Creating generative AI models
To build a decision service, you might need to analyze or generate specific content based
on the context of the decision service itself. You can specify what needs to be analyzed and
produced by using the prompt editor. You can then use the content within decision
models.
When you use decision automation to complete your tasks, some decision automations are automating your tasks, such as making a custom quotation, getting it approved, and notifying customers. In this process, you might need to understand or produce contextual information.
For example:
- Generate more information about the target customer when the quotation is created.
- Generate an explanation of why specific terms and conditions are added to the quotation.
- Generate email text that is sent to the customer with the appropriate information and tone.
All these examples are contextual, and might vary from one execution to the next. Each decision service execution must take this context into account to analyze or generate the information.
For a complete example of how to work with generative AI models, see the
Using generative AI to support decisions sample available on GitHub
. Alternatively, you can import the
Training sample from the Samples library in Decision Designer.